This project titled 'Validating resting state fMRI derived brain connectivity'represents a large scale effort to establish rigorously the reliability of brain connectivity measures derived from resting state fMRI (fcMRI). This method of studying the spatial pattern of connectivity between regions of the brain has recently seen an intensive period of growth. Recent publications indicate the method may be able to give insight into the large scale structure of interactions between brain regions that support the integrated functioning of the brain in human health. There is also a growing body of literature that indicates deviations from the normally observed pattern of connectivity may be a fundamental causative factor in many mental health disorders including schizophrenia, depression, and autism. In applying this method there are a large number of processing steps that must be applied to the data before the statistical measures of connectivity are calculated. There is currently a lack of knowledge as to the effects of different methods of preprocessing on the reliability of the results obtained using fcMRI. One type of processing required involves the removal of variations in the signal resulting from cardiac and respiratory induced pulsations in the brain. Currently simple digital filtering methods are usually used. Theoretical considerations indicate this type of processing may not give optimal results. This study will investigate the improvements that may be achieved by using more complex methods that involve utilizing recordings of the cardiac and respiratory cycle measured from the subject at the time of MRI scanning. Another factor that influences the accuracy and reliability of the results concerns processing that must be performed in order that comparisons between subjects may be made. In order that comparisons may be made between corresponding brain regions of different subjects the brain scans must be brought into alignment. It is well known in the neuroscience community that the different mathematical tools used to accomplish this are imperfect and that different methods introduce different errors. This study will investigate the differences in reliability that result from the application of the different methods to accomplish this alignment. In order that the results of the study will be sufficiently general to serve as a guide for investigators we will acquire fcMRI data from a large number of healthy individuals and use a study design known as a bootstrap design. Multiple MRI data sets will be acquired from each of approximately 100 volunteers. The data from all subjects will be processed with each of the different processing methods considered in the study. The methodology follows a procedure of choosing subsets of the subjects and calculating fcMRI measures. Next measures of the intra subject and intersubject reliability are calculated from the proceeding results. This basic procedure is repeated a large number of times building a large set of measurements from which reliable statistics may be calculated. The results derived from this study will serve to enable researchers in the field of fcMRI to conduct more informed study design and aid in the interpretation of the validity of results. This study represents an essential next step in the validation of fcMRI as a biomarker for the characterization of normal and pathological brain function. The research is intended to validate the results of an emerging method known as resting state fmri in understanding human and animal brain connectivity. It would serve to guide practitioners of the technical requirements for achieving optimal results utilizing this method. This proposed research contributes to both basic neuroscience and clinical neuroscience and will provide the foundation for future studies characterizing brain connectivity in normals and disruptions of connectivity in various patient populations.